The invention relates to a method and a system of iteratively detecting and decoding received symbols, coupled with a re-estimation of the coefficients of the transmission channel.
In the field of mobile wireless telephony, it is imperative that the process used to detect and decode transmitted symbols, by channel encoding and modulation of a carrier wave, should take account of the interactions of the transmission channel in order to minimize the effects of the latter and obtain a satisfactory reception quality.
Whilst the transmission channel exhibits radio-electric characteristics during transmission of the symbols and hence a transfer function which is variable over time, the receivers available these days use either a process of optimum detection and decoding, in which case almost perfect equalization of the effects of this transmission channel are obtained, or a process of sub-optimum detection and decoding, whereby an iteration of the detection and decoding method makes it possible to come close to an almost perfect equalization of the effects of the transmission channel.
At present, it has proved almost impossible to use optimum detection and decoding processes because of the very high complexity of the computations needed, particularly in the case of transmission channels with too long a pulse response, as is the case in an urban environment, for example.
The sub-optimum detection and decoding process likely to be used with receivers of the evolved GSM type (EDGE) in current usage is based, for example, on a sub-optimum equalization process known as DDFSE (which stands for Delayed Decision Feedback Sequence Estimator), this process involving the use of pre-filtering, the purpose of which is to place the estimated transmission channel in minimum phase. It will be recalled that a minimum phase transmission channel can be likened to a filter which permits the transmission of time components whose energy is concentrated in the first coefficients of this filter, corresponding to the shortest delays.
For a more detailed description of the DDFSE equalization process, it may be useful to refer to the articles entitled:                “Delayed Decision-Feedback Sequence Estimation”, published by A. DUEL-HALLEN, C. HEEGARD—IEEE Trans. on Commun., vol. 37, pp. 428–436, May 1989;        “Filtre correcteur de phase pour égaliseurs sous-optimaux”, published by A. WAUTIER, J. C. DANY, C. MOUROT, Annales de Télécommunications, no. 9–10, 1992.        
Referring to the above-mentioned articles, FIG. 1a provides an illustration showing an example of a receiver likely to be used for a DDFSE equalization process with weighted outputs and a convolutional decoder of the Viterbi type. A module which de-interleaves the weighted outputs, denoted by Π−1, enables account to be taken of the process used to interleave the symbols prior to coding as well as the process used to transmit the latter.
The principle of detection and decoding by iteration, also known as “turbo-detection”, was initially proposed by C. DOUILLARD, M. JEZEQUEL, C. BERROU, A. PICART, P. DIDIER, A. GLAVIEUX in an article entitled “Iterative Correction of Intersequential Interference: Turbo-Equalization” and published by European Transactions on Telecommunications, vol. 6, pp. 507 to 511, September 1995.
In this detection and decoding method, the equalization process is based on an equalizer of maximum likelihood, with weighted inputs and outputs, referred to as SISO MLSE, whilst the convolutional decoding process used is based on a Viterbi process with weighted inputs and outputs, known as SOVA. The SOVA decoding process was described in a publication entitled “A Low Complexity Soft Output Viterbi Decoder Architecture”, ICC'93, pp. 733 to 740, Geneva, Switzerland, May 1993.
Since then, there have been extensive developments to the above-mentioned detection and decoding process, which have led to the use of optimum detectors based on maximum a posteriori probability (MAP). For a more detailed description of optimum detectors of these types, reference should be made to the articles entitled:                “Optimal Decoding of Linear Codes for Minimizing Symbol Error Rate”, published by L. R. BAHL, J. COCKE, F. JELINEK, J. RAVIV, edited by IEEE Transactions on Information Theory, vol. IT-20, pp. 284–287, March 1994;        “Iterative Equalization and Decoding in Mobile Communications Systems”, published by G. BAUCH, H. KHORRAM, J. HAGENAUER in Proc. EPMCC'97, pp. 307–312, Bonn, Germany, September 1997.        
Whereas the turbo-detection process mentioned above effectively cancels out intersymbol interference (ISI) introduced by the effect of the transmission channel, assuming a perfect estimation of the channel coefficients and a sufficient inter-leaving depth of the symbols, an irreversible deterioration of 2.5 to 3 dB nevertheless occurs in the binary error rate if the coefficients of the transmission channel are initially estimated with noise. Reference should be made to the article entitled “A Comparison of Soft-In-Soft-Out Algorithms for Turbo-Detection”, published by G. BAUCH, V. FRANZ, International Conference on Telecommunications (ICT), vol. 2, pp. 259 to 263, Portos Caras, Greece, June 1998.
Finally, a new method of applying symbol detection and channel decoding methods by iteration, known as the turbo-equalization process and substantially different from the above-mentioned turbo-detection process, was proposed in 1997. Reference should be made to the article entitled “Turbo-Equalization over Frequency Selective Channel”—International Symposium on Turbo-Codes, Brest, France, September 1997.
Generally speaking, it may be said that the above-mentioned turbo-equalization process assumes, in essence, a noise estimation of the transmission channel. Although this turbo-equalization process appears promising in the case of modulations with a high spectral efficiency, it nevertheless seems to introduce a deterioration in performance, which is largely dependent on the type of equalization process used for the first iteration, as compared with the turbo-detection process with a noise estimation. Reference should be made to the article entitled “Joint Equalization and Decoding: Why Choose the Iterative Solution ?”, published by A. ROUMY, I. FIGALKOW, D. PIREZ, IEEE VTC'1999 Fall, Amsterdam, Netherlands, September 1999.